45 pages • 1 hour read
Darrell HuffHow to Lie with Statistics
Nonfiction | Reference/Text Book | Adult | Published in 1954A modern alternative to SparkNotes and CliffsNotes, SuperSummary offers high-quality Study Guides with detailed chapter summaries and analysis of major themes, characters, and more.
Chapter 8Chapter Summaries & Analyses
Chapter 8 Summary: “Post Hoc Rides Again”
Chapter 8 deals with the issue of the post hoc fallacy and the problem of thinking correlation equals causation. Huff says this occurs when one of two items with a demonstrable correlation is assumed to cause the other. He describes the thought process as “If B follows A, then A has caused B” (89). However, this is not necessarily the case. Other factors might cause “B,” while “A” is not responsible for them.
Huff begins with a study on whether cigarette smokers get lower grades. He says the sample size and the significance of the correlation are good, but it needs to account for other explanations that could cause both smoking and low grades. Without a clear understanding of these unknown factors, conclusions about causation should not be drawn.
In the next section, Huff warns readers to carefully examine the relationship underlying any statistics to ensure they don’t fall for the fallacy. He then lays out the different types of correlation that can appear as causation. One is correlations made by chance, such as those found in small samples. Another is a correlation that has a real relationship but no way to tell which factor is the cause or the effect. Huff takes particular interest in scenarios in which there is a real correlation between elements but neither affects the other. For example, he cites the correlation between the high number of both weddings and attempts at suicide in the month of June. He argues against the former causing the latter and suggests that emotional issues regarding seasons may be an underlying factor.
Huff warns that even if a correlation between variables exists, it may still have no value. This is because the conclusions drawn may still be incorrect. Huff concludes by emphasizing the importance of being critical of statistics being used to muddy the relationship between cause and effect.
Chapter 8 Analysis
The focus of this chapter is that the post hoc fallacy (or correlation not equaling causation) is a critical element in understanding this book and statistics as a whole. Just because two variables often appear together does not mean one causes the other. As Huff points out, the two points often result from the same outside factor. However, because the first two variables possess a demonstrable connection, that connection can be leveraged to prove a point. In most cases, the belief in a cause-and-effect relationship stems from a need for more information on, or a refusal to acknowledge, the broader scope of the topic. Social or economic trends influence far more realms than one might assume.
This chapter, like the previous one, focuses on leaps of logic taken to present a desired narrative, but it focuses less on explaining statistical terminology. Instead, Huff takes his time examining and unpacking faulty conclusions. He again returns to statistics on smokers, this time focusing on debunking statistics that purport to show that smoking causes worse grades in students. He proposes several alternatives for the correlation, some of which he admits are supported by more evidence than others. Most of his examples in this chapter follow this structure and build on his warning that many alternative explanations exist for the correlations.
In his example of the statistics regarding death by suicide, Huff fails to approach this issue with sensitivity and respect. As with his other examples, he proposes his reason for this outcome with his typically irreverent writing style. This is despite his acknowledgment that his guess is as untested as the cause he discredits.
